Robot Learning and Control

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Related lectures (31)

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Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.

Force Control with Dynamical Systems

Covers compliant and force control for robots using Dynamical Systems.

Compliant Control for Robots: Impedance and Variable Stiffness

Explores compliant control for robots through impedance and variable stiffness, enabling safe and adaptive interactions with the environment.

Obstacle Avoidance with DS

Explores obstacle avoidance using Dynamical Systems for robots, focusing on modulation, stability guarantees, and contraction theory.

Learning Modulation for DS

Explores learning and adaptive control for robots, emphasizing modulation of dynamical systems to improve stability and enable reactive motion.

Learning and Adaptive Control for Robots: SEDS & LPV-DS

Explores learning and adaptive control for robots through SEDS and LPV-DS, emphasizing stability, non-linear dynamics, and optimization.

Learning and Adaptive Control for Robots: Overview and Path Planning

Explores learning and adaptive control for robots, focusing on challenges, path planning with dynamical systems, and real-time planning applications.

Learning Physically-Consistent Gaussian Mixture Model

Explores Physically-Consistent Gaussian Mixture Models for robot control and trajectory learning.

Learning and Adaptive Control for Robots: Extensions to DS

Explores coupled and uncoupled dynamical systems, stability, hand-arm coupling, and adaptation in robotics.

Improving Robot Design: Data-Driven Approaches

Explores data-driven approaches to improve robot design, focusing on compliance, soft materials, and complex interactions.